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首页> 外文期刊>International Journal on Computer Science and Engineering >Probability Measure of Navigation pattern predition using Poisson Distribution Analysis
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Probability Measure of Navigation pattern predition using Poisson Distribution Analysis

机译：基于泊松分布分析的导航模式掠夺概率测度

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The World Wide Web has become one of the most important media to store, share and distribute information. The rapid expansion of the web has provided a great opportunity to study user and system behavior by exploring web access logs. Web Usage Mining is the application of data mining techniques to large web data repositories in order to extract usage patterns. Every web server keeps a log of all transactions between the server and the clients. The log data which are collected by web servers contains information about every click of user to the web documents of the site. The useful log information needs to be analyzed and interpreted in order to obtain knowledge about actual user preferences in accessing web pages. In recent years several methods have been proposed for mining web log data. This paper addresses the statistical method of Poisson distribution analysis to find out the higher probability session sequences which is then used to test the web application performance. The analysis of large volumes of click stream data demands the employment of data mining methods. Conducting data mining on logs of web servers involves the determination of frequently occurring access sequences. A statistical poisson distribution shows the frequency probability of specific events when the average probability of a single occurrence is known. The Poisson distribution is a discrete function wich is used in this paper to find out the probability frequency of particular page is visited by the user.
机译：万维网已经成为存储，共享和分发信息的最重要的媒体之一。 Web的迅速扩展为通过浏览Web访问日志来研究用户和系统行为提供了巨大的机会。 Web使用情况挖掘是将数据挖掘技术应用于大型Web数据存储库，以提取使用模式。每个Web服务器都保留服务器和客户端之间所有事务的日志。 Web服务器收集的日志数据包含有关用户每次单击站点Web文档的信息。需要分析和解释有用的日志信息，以便获得有关访问网页时实际用户偏好的知识。近年来，已经提出了几种用于挖掘Web日志数据的方法。本文介绍了泊松分布分析的统计方法，以找出较高概率的会话序列，然后将其用于测试Web应用程序的性能。对大量点击流数据的分析要求采用数据挖掘方法。在Web服务器的日志上进行数据挖掘涉及确定频繁发生的访问顺序。统计泊松分布表示已知单个事件的平均概率时特定事件的频率概率。泊松分布是本文使用的离散函数，用于找出用户访问特定页面的概率频率。

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